@@ -3282,10 +3282,56 @@ def errorbar(self, x, y, yerr=None, xerr=None,
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x = np .asarray (x , dtype = object )
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if not isinstance (y , np .ndarray ):
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y = np .asarray (y , dtype = object )
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+
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+ def _upcast_err (err ):
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+ """
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+ Safely handle tuple of containers that carry units.
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+
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+ If the units are carried on the values then casting to object
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+ arrays preserves the units, but if the units are on the containers
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+ this will not work.
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+
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+ This function covers the case where the input to the xerr/yerr is a
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+ length 2 tuple of equal length ndarray-subclasses that carry the
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+ unit information in the container.
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+
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+ We defer coercing the units to be consistent to the underlying unit
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+ library (and implicitly the broadcasting).
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+
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+ If we do not have a tuple of nested numpy array (subclasses),
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+ fallback to casting to an object array.
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+
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+ """
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+
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+ # we are here because we the container is not a numpy array, but it
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+ # _is_ iterable (likely a list or a tuple but maybe something more
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+ # exotic)
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+
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+ if (
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+ # make sure it is not a scalar
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+ np .iterable (err ) and
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+ # and it is not empty
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+ len (err ) > 0 and
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+ # and the first element is an array sub-class use
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+ # safe_first_element because getitem is index-first not
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+ # location first on pandas objects so err[0] almost always
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+ # fails.
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+ isinstance (cbook .safe_first_element (err ), np .ndarray )
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+ ):
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+ # grab the type of the first element, we will try to promote
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+ # the outer container to match the inner container
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+ atype = type (cbook .safe_first_element (err ))
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+ # you can not directly pass data to the init of `np.ndarray`
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+ if atype is np .ndarray :
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+ return np .asarray (err , dtype = object )
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+ # but you can for unyt and astropy uints
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+ return atype (err )
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+ return np .asarray (err , dtype = object )
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+
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if xerr is not None and not isinstance (xerr , np .ndarray ):
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- xerr = np . asarray (xerr , dtype = object )
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+ xerr = _upcast_err (xerr )
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if yerr is not None and not isinstance (yerr , np .ndarray ):
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- yerr = np . asarray (yerr , dtype = object )
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+ yerr = _upcast_err (yerr )
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x , y = np .atleast_1d (x , y ) # Make sure all the args are iterable.
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if len (x ) != len (y ):
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raise ValueError ("'x' and 'y' must have the same size" )
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